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Spotlight
PAGE: https://alison.com/course/diploma-in-software-testing-revised
PROMISE: Gain formal CPD accreditation to prove the team has mastered software testing fundamentals.
WHO: Small business teams seeking formal credentials to validate their testing fundamentals.
WHYNOW: Adopting AI automation tools without a strong testing foundation often results in low-quality tests.
DESC: Learn all about Software Testing in this course. Topics cover levels of testing, the pesticide effect, special value testing and Dataflow testing.
BEFORE: Team testing knowledge is informal and inconsistent across members.
BEFORE: There is no shared vocabulary for verification versus validation.
BEFORE: Test case design relies on intuition rather than systematic approaches.
AFTER: Team holds CPD-accredited proof of fundamental testing knowledge.
AFTER: Staff clearly separate verification from validation in their workflows.
AFTER: Test cases are designed using recognized systematic approaches.
GAIN: Formal CPD accreditation proving the team covered core testing concepts.
GAIN: Ability to clearly separate verification from validation in daily tasks.
GAIN: Knowledge of systematic test case design approaches to reduce blind spots.
STEP: The team claims they understand testing but cannot define key terms or justify their methods. || Having completed this course, you will be able to: || The team completes the course structure to build a baseline of knowledge before attempting complex tasks.
STEP: Junior staff struggle to distinguish between confirming the build and confirming the user need. || Distinguish between the verification and validation process in software testing || Staff apply the correct terminology when documenting why a bug fails the build versus why it fails user expectations.
STEP: Test cases seem arbitrary, and the team does not know how to systematically reduce risk. || Identify the main approaches to designing a test case || The team selects a structured design approach instead of relying on ad-hoc guessing for test coverage.
STEP: The team runs the same tests repeatedly until the software becomes immune to those specific checks. || Describe the pesticide effect in testing software || Leaders rotate test strategies to avoid the blind spots that develop when the same tests are used indefinitely.
NOTFOR: Experienced engineers who need advanced automation frameworks or cloud DevOps skills.
NOTFOR: Teams looking for hands-on coding labs in specific languages like Java or Python.
FACT: Average duration: 10-15 Hours (Contains Video)
FACT: CPD-accredited certificate available
FACT: Beginner level
COVERS: Having completed this course, you will be able to:
COVERS: Identify ways of reducing bugs in your software program
COVERS: Distinguish between the verification and validation process in software testing
COVERS: Describe the pesticide effect in testing software
COVERS: Outline what unit testing is and when it is performed
COVERS: Identify the main approaches to designing a test case
COVERS: Discuss the use of equivalence class testing
COVERS: Define special value testing and pair-wise testing
COVERS: Discuss White-box testing and its types of strategies
COVERS: Outline the different types of condition coverage testing
COVERS: Explain path coverage testing and creation of control-flow graphs
COVERS: Discuss what Dataflow testing involves
MODULE: Introduction to Levels of Testing || Introduction to Software Testing | Levels of Testing
MODULE: Basic Concepts in Testing and Unit Testing || Basic Concepts in Testing – Part I | Basic Concepts in Testing – Part 2 | Unit Testing
MODULE: Equivalence and Special Value Testing || Equivalence and BV Testing | Special Value Testing
MODULE: Combinatorial and White-Box Testing || Combinatorial Testing | Pairwise Testing | White-Box Testing
MODULE: MC/DC Testing || MC/DC Testing – Part 1 | MC/DC Testing – Part 2
MODULE: Path, Dataflow and Mutation Testing || Path Testing | Dataflow and Mutation Testing | Mutation Testing
MODULE: Introduction to Testing Levels || Integration Testing | System Testing | Regression Testing
MODULE: Testing Object-Orientated Programs || Testing Object-Oriented Programs – Part 1 | Testing Object-Oriented Programs – Part 2
What you are probably seeing
Your dashboard shows a high volume of newly generated test cases but the bug detection rate remains flat or declines.
Manual reviews of these automated tests reveal vague assertions that do not verify actual business logic or user outcomes.
Why it happens
AI agents operate without intrinsic business context and rely entirely on the quality of the patterns and examples provided by the team.
When the underlying staff lacks the skill to distinguish between a passing test and a meaningful one, the tool scales the error rather than the fix.
What changed recently
Step by step
1. Audit your current test suite to categorize tests by their ability to catch specific defects rather than just execution status.
2. Require developers to write one manual test that simulates a critical failure scenario before automating it with AI.
3. Establish a definition of done that includes test maintainability and clarity, not just coverage percentage.
4. Conduct a peer review session where the team explains the intent behind a specific test case to verify understanding.
5. Pilot the AI tool on a single module to measure the reduction in false positives before wider deployment.
Ways to go further
Start here: Diploma in Software Testing For when You want formal credentials to prove the team has mastered the testing fundamentals.. Open the free course on Alison ↗
Better fit: Leveraging AI in Predictive Analytics, Automation, and Data Management For when You are ready to integrate AI but need to understand how it handles data and automation risks.. Open the free course on Alison ↗
Best when: Introduction to Software Testing For when You need to rebuild the foundation of how the team defines and writes tests.. Open the free course on Alison ↗
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